Advancements in computer and networking technologies have enabled persons to conduct commercial and financial transactions “on-line” via computer-based applications. This has given rise to a new era of electronic commerce (often referred to as e-commerce.) A number of well-known retailers have expanded their presence and reach by operating websites that facilitate e-commerce. In addition, many new retailers, which operate exclusively online, have come into existence. The business models utilized by enterprises operating online are almost as varied as the merchandise and services being offered. For instance, some merchandise and services are offered at fixed prices, while others are offered via various auction methods, and still others are offered via a system of classified ad listings. Some enterprises specialize in the selling of a specific type of merchandise (e.g., books) or a specific service (e.g., tax preparation), while others provide a myriad of categories of merchandise and services from which to choose. Some enterprises sell directly to consumers while others serve only as an intermediary, connecting sellers and buyers. Despite the many technical advances that have improved the state of e-commerce, a great number of technical challenges and problems remain.
One such problem involves determining how to best present search results (e.g., merchandise listings, web pages, advertisements) in the search results page (or pages), when the search results have heterogeneous types. For example, the search results may include merchandise listings being offered via auctions, as well as merchandise listings being offered at fixed prices. In this context, the type of the listing is the price mechanism used to offer the item for sale. In some instances, the merchandise listings may have different sources. For example, some merchandise listings may be classified ad listings retrieved from a first source, such as a web site dedicated to classified ad listings, while other merchandise listings may be retrieved from a different online source, such as specialty retail web sites. In this context, the type of listing depends on the source of the listing. In yet another example of different listing types, in some instances, some of the merchandise listings will be for unique items for which there is no matching product in a product catalog maintained by the e-commerce system, while other merchandise listings will be for products, for example, selected from a catalog of products maintained by the e-commerce system.
When these scenarios arise, it can often be difficult to determine how best to position the different types of search results with respect to one another in the search results page (or, pages). One of the reasons it may be difficult to mix the search results and present them in the search results page (or, pages) in an intermingled manner is that the data used to rank or rate the individual listings may not be available for one or the other listings types. In some instances, because of a different ranking algorithm for ranking the two different listing types, the data used for ranking a first listing type may be different from the data used in ranking the second listing type. Accordingly, a fair comparison of the relative quality of two different listings having different listing types may not be readily available.
A particular instance of this problem occurs with item listings and product listings displayed in the search results pages of an e-commerce platform that serves as intermediary connecting sellers with buyers. For instance, some of the merchandise listings generated by the sellers may be for unique items with unique attributes (e.g., color, size, features, and so forth), while other items may match a known product in a catalog system of the e-commerce platform. Accordingly, when a seller is listing a unique item for which there is no match in the e-commerce platform's product catalog, the seller must provide all of the item attribute information including a photograph of the item. When the seller is listing an item known to match an existing product from the catalog, the seller can simply specify the product and the e-commerce platform can automatically provide the product attributes for the listing, including a stock photo for the product. When presenting search results for a particular user-initiated search, the search results may contain merchandise listings for unique items not associated with any particular product, referred to herein as item listings, and merchandise listings that are associated with particular products, referred to herein as product listings.
Just as product placement in a retail store can greatly affect the level of sales for a particular product, in the e-commerce context, it is well known that merchandise listings that appear in the most prominent positions of a search results page will have a greater conversion rate. Accordingly, it is common for e-commerce platforms to utilize ranking or ordering algorithms in conjunction with search engines in an attempt to position the best merchandise in the most prominent positions (e.g., typically, the top of a list) of the search results pages. One way this is achieved is to monitor user activities associated with merchandise listings, and use certain activities as a proxy for demand. For example, if a particular merchandise listing is frequently selected (e.g., clicked on) when presented in the search results pages, this may indicate that the merchandise listing is a highly sought after item, and therefore should be presented prominently in the search results. However, when the volume of unique item listings being managed by the e-commerce platform reaches a certain threshold, it becomes extremely difficult and cost prohibitive to monitor and store the information required to assess the demand (based on user activity) of every unique item listing. Consequently, when the listings are of two different types, such as product listings and item listings, applying a uniform scoring and ranking algorithm to determine the order in which the listings should be presented in a set of search results pages becomes a non-trivial task.